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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

No Launch Before Its Time

Aura is an Earth-observing satellite developed to help us study the quality of the air we breathe. It will look at the state of the ozone and the atmospheric composition in regards to the Earth's changing climate. I headed to California on July 5, 2004. The plan was that the satellite would launch on the tenth, but we had a few problems getting it off. This was the fifty-ninth launch of my career, and it was also a little different than most of my previous launches. Most of the time it's weather that postpones a launch; there aren't usually that many technical issues this late in the game. This time. however, we had several problems, equally split between the launch vehicle and the spacecraft. I remember a member of the crew asking me, 'Is this normal?' And in my experience, it wasn't.

Townsend, Bill↗
DOE OSTI2023

Stratosphere-Troposphere Coupling of Extreme Stratospheric Wave Activity in CMIP6 Models

Extreme stratospheric wave activity has been suggested to be connected to surface temperature anomalies, but some key processes are not well understood. Using observations, we show that the stratospheric events featuring weaker-than-normal wave activity are associated with increased North American (NA) cold extreme risks before and near the event onset, accompanied by less frequent atmospheric river (AR) events on the west coast of the United States. Strong stratospheric wave events, on the other hand, exhibit a tropospheric weather regime transition. Further, they are preceded by NA warm anomalies and increased AR frequency over the west coast, followed by increased risks of NA cold extremes and north-shifted ARs over the Atlantic. Moreover, these links between the stratosphere and troposphere are attributed to the vertical structure of wave coupling. Weak wave events show a wave structure of westward tilt with increasing altitudes, while strong wave events feature a shift from westward tilt to eastward tilt during their life cycle. This wave phase shift indicates vertical wave coupling and likely regional planetary wave reflection. Further examinations of CMIP6 models show that models with a degraded representation of stratospheric wave structure exhibit biases in the troposphere during strong wave events. Specifically, models with a stratospheric ridge weaker than the reanalysis exhibit a weaker tropospheric signal. Our findings suggest that the vertical coupling of extreme stratospheric wave activity should be evaluated in the model representation of stratosphere-troposphere coupling.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Some effects of adverse weather conditions on performance of airplane antiskid braking systems

The performance of current antiskid braking systems operating under adverse weather conditions was analyzed in an effort to both identify the causes of locked-wheel skids which sometimes occur when the runway is slippery and to find possible solutions to this operational problem. This analysis was made possible by the quantitative test data provided by recently completed landing research programs using fully instrumented flight test airplanes and was further supported by tests performed at the Langley aircraft landing loads and traction facility. The antiskid system logic for brake control and for both touchdown and locked-wheel protection is described and its response behavior in adverse weather is discussed in detail with the aid of available data. The analysis indicates that the operational performance of the antiskid logic circuits is highly dependent upon wheel spin-up acceleration and can be adversely affected by certain pilot braking inputs when accelerations are low. Normal antiskid performance is assured if the tire-to-runway traction is sufficient to provide high wheel spin-up accelerations or if the system is provided a continuous, accurate ground speed reference. The design of antiskid systems is complicated by the necessity for tradeoffs between tire braking and cornering capabilities, both of which are necessary to provide safe operations in the presence of cross winds, particularly under slippery runway conditions.

Horne, W. B.↗
NASA NTRS2022

Satellite-Based Characterization of Convection and Impacts from the Catastrophic 10 August 2020 Midwest U.S. Derecho

The catastrophic derecho that occurred on 10 August 2020 across the Midwest United States caused billions of dollars of damage to both urban and rural infrastructure as well as agricultural crops, most notably across the state of Iowa. This paper documents the complex evolution of the derecho through the use of low-Earth orbit passive-microwave imager and GOES-16satellite-derived products complemented by products derived from NEXRAD weather radar observations. Additional satellite sensors including optical imagers and synthetic aperture radar (SAR) were used to observe impacts to the power grid and agriculture in Iowa. SAR improved the identification and quantification of damaged corn and soybeans, as compared to true-color composites and Normalized Difference Vegetation Index (NDVI). A statistical approach to identify damaged corn and soybean crops from SAR was created with estimates of 1.97 million acres of damaged corn and 1.40 million acres of damaged soybeans in the state of Iowa. The damage estimates generated by this study were comparable to estimates produced by others after the derecho, including two commercial agricultural companies.

Derecho↗
NASA NTRS2003

Predictability of Malaria Transmission Intensity in the Mpumalanga Province, South Africa, Using Land Surface Climatology and Autoregressive Analysis

There has been increasing effort in recent years to employ satellite remotely sensed data to identify and map vector habitat and malaria transmission risk in data sparse environments. In the current investigation, available satellite and other land surface climatology data products are employed in short-term forecasting of infection rates in the Mpumalanga Province of South Africa, using a multivariate autoregressive approach. The climatology variables include precipitation, air temperature and other land surface states computed by the Off-line Land-Surface Global Assimilation System (OLGA) including soil moisture and surface evaporation. Satellite data products include the Normalized Difference Vegetation Index (NDVI) and other forcing data used in the Goddard Earth Observing System (GEOS-1) model. Predictions are compared to long- term monthly records of clinical and microscopic diagnoses. The approach addresses the high degree of short-term autocorrelation in the disease and weather time series. The resulting model is able to predict 11 of the 13 months that were classified as high risk during the validation period, indicating the utility of applying antecedent climatic variables to the prediction of malaria incidence for the Mpumalanga Province.

Grass, David↗
NASA NTRS2014

Satellite Sounder Data Assimilation for Improving Alaska Region Weather Forecast

Data assimilation has been demonstrated very useful in improving both global and regional numerical weather prediction. Alaska has very coarser surface observation sites. On the other hand, it gets much more satellite overpass than lower 48 states. How to utilize satellite data to improve numerical prediction is one of hot topics among weather forecast community in Alaska. The Geographic Information Network of Alaska (GINA) at University of Alaska is conducting study on satellite data assimilation for WRF model. AIRS/CRIS sounder profile data are used to assimilate the initial condition for the customized regional WRF model (GINA-WRF model). Normalized standard deviation, RMSE, and correlation statistic analysis methods are applied to analyze one case of 48 hours forecasts and one month of 24-hour forecasts in order to evaluate the improvement of regional numerical model from Data assimilation. The final goal of the research is to provide improved real-time short-time forecast for Alaska regions.

Zhu, Jiang↗
NASA NTRS1986

Extensional tectonics during the igneous emplacement of the mafic-ultramafic rocks of the Barberton greenstone belt

The simatic rocks (Onverwacht Group) of the Barberton greenstone belt are part of the Jamestown ophiolite complex. This ophiolite, together with its thick sedimentary cover occupies a complex thrust belt. Field studies have identified two types of early faults which are entirely confined to the simatic rocks and are deformed by the later thrusts and associated folds. The first type of fault (F1a) is regional and always occurs in the simatic rocks along and parallel to the lower contacts of the ophiolite-related cherts (Middle Marker and equivalent layers). These fault zones have previously been referred to both as flaser-banded gneisses and as weathering horizons. In general the zones range between 1-30m in thickness. Displacements along these zones are difficult to estimate, but may be in the order of 1-100 km. The structures indicate that the faults formed close to horizontal, during extensional shear and were therefore low angle normal faults. F1a zones overlap in age with the formation of the ophiolite complex. The second type of faults (F1b) are vertical brittle-ductile shear zones, which crosscut the complex at variable angles and cannot always be traced from plutonic to overlying extrusive (pillowed) simatic rocks. F1b zones are also apparently of penecontemporaneous origin with the intrusive-extrusive igneous processs. F1b zones may either represent transform fault-type activity or represent root zones (steepened extensions) of F1a zones. Both fault types indicate extensive deformation in the rocks of the greenstone belt prior to compressional overthrust tectonics.

Dewit, M. J.↗
NASA NTRS2016

Predictions of Solar Cycle 24: How are We Doing?

Predictions of solar activity are an essential part of our Space Weather forecast capability. Users are requiring usable predictions of an upcoming solar cycle to be delivered several years before solar minimum. A set of predictions of the amplitude of Solar Cycle 24 accumulated in 2008 ranged from zero to unprecedented levels of solar activity. The predictions formed an almost normal distribution, centered on the average amplitude of all preceding solar cycles. The average of the current compilation of 105 predictions of the annual-average sunspot number is 106 +/- 31, slightly lower than earlier compilations but still with a wide distribution. Solar Cycle 24 is on track to have a below-average amplitude, peaking at an annual sunspot number of about 80. Our need for solar activity predictions and our desire for those predictions to be made ever earlier in the preceding solar cycle will be discussed. Solar Cycle 24 has been a below-average sunspot cycle. There were peaks in the daily and monthly averaged sunspot number in the Northern Hemisphere in 2011 and in the Southern Hemisphere in 2014. With the rapid increase in solar data and capability of numerical models of the solar convection zone we are developing the ability to forecast the level of the next sunspot cycle. But predictions based only on the statistics of the sunspot number are not adequate for predicting the next solar maximum. I will describe how we did in predicting the amplitude of Solar Cycle 24 and describe how solar polar field predictions could be made more accurate in the future.

Pesnell, William D.↗
NASA NTRS1982

Image-data-processing for earth resources - An overview

A total remote-sensing system comprises four distinct operations: data-acquisition, archiving, production, and dissemination of individual products, and extraction of the required information. The Landsat satellite system acquires data in several spectral bands, with a ground resolution of 80 meters (currently) or 30 meters (future). Radiometric and geometric corrections are normally applied, after which the data may be enhanced for photointerpretation or analyzed by computer. The accuracy of the analysis model for either is important. The extraction of information from remotely sensed data will generally be dependent on the use of it with other data such as maps or, perhaps, weather information. Methods are being developed to use the various data together in geographic data systems. The availability of remotely sensed data has encouraged the development of new models or analysis procedures for the use of this information.

Billingsley, F. C.↗
NASA NTRS1979

An auroral effect on the fair weather electric field

Evidence is presented for coupling between the upper and lower atmosphere by means of the shorting out of the vertical mesospheric electric field by auroral radiation, which causes a transfer of mesospheric potential to the lower atmosphere. Measurements were made by an electric field antenna which was part of a parachute-borne payload, launched by rocket from near Fairbanks, Alaska. Data obtained from quiet time observations indicate the normal low altitude electric field pattern, with a greater field at high altitudes, while observations at disturbed times show a small field at high altitudes and a greater field at low altitudes. Means for observing this effect at lower latitudes are also suggested. While the data obtained support the proposed mechanism, it is noted that other mechanisms, such as direct modulation by large amounts of solar cosmic rays and aurorally produced charge separation, may also be important.

Hale, L. C.↗
DOE OSTI2021

HAIMOS Ensemble Forecasts for Intra-day and Day- Ahead GHI, DNI and Ramps

The objective of this research is to develop a hybrid physics-based/data-driven forecast model to improve direct normal and global horizontal irradiance (DNI and GHI) prediction for horizons ranging from 1 to 72 hours. Project objectives also address key gaps in state-of-the-art solar forecasting: accurate probabilistic solar forecasts and the forecasting of large irradiance ramps (ramp onset and magnitude). The proposed model ensembles Numerical Weather Prediction (NWP) forecasts, determinist physics-based algorithms, and new-generation cloud cover products (high-resolution rapid refresh satellite images and Large Eddy Simulations). The result is the Hybrid Adaptive Input Model Objective Selection (HAIMOS) ensemble model. HAIMOS blends state of the art machine learning methodologies with physics-based models for cloud cover and cloud optical depth forecasts. The technical activities followed a two-pronged strategy. First, the preprocessing of data, the selection of inputs to the nonlinear approximators, the type of approximator and objective functions, and post-processing ensembling techniques included in HAIMOS were all optimized adaptively to find the best model for a specific goal (reduce DNI/GHI forecast error, improve the prediction of ramp onset, etc.). Second, a large effort was put in improving cloud identification and the forecast of cloud cover and cloud optical depth. To this end, new-generation cloud parametrization products were developed in this work. These include improved algorithms to assist in cloud identification, cloud classification and cloud parametrization from satellite images – three key factors in the accuracy of 1 to 6-hours irradiance forecasts and prediction of ramp onset. Furthermore, we also included cloud information extracted from high resolution rapid refresh satellite images (GOES-16) and Large Eddy Simulations (LES). LES was used to model the atmosphere in detail over locations of interest and produce cloud optical depth forecasts. Once these data streams were validated, they were used as input data to the HAIMOS forecast. The model was developed using data from several climatologically distinct locations with potential for high solar penetration. In the last year of the project, we conducted a validation campaign according to the guidelines stipulated by the Topic Area 1 project as described in the FOA. This effort brings, for the first time, proven machine-learning methodologies for generating state-of-the-art solar forecasts interweaved with detailed physics-based models for cloud detection, and cloud optical depth forecasts. HAIMOS will generate accurate irradiance probabilistic forecast to assist in reducing solar generation prediction error. Globally optimized solar forecast models are more likely to impact solar energy stakeholders. The goal of this project was to increase the state-of-the-art forecast skill from their present values of 10 to 35%. At the end of the project, we achieved between 30% and 50% forecast skill across a wide range of horizons for both GHI and DNI.

14 SOLAR ENERGY↗
NASA NTRS1985

A monthly forecast experiment: Preliminary report

An experiment on monthly forecasts with eight winter cases is being carried out, using a 1980 general circulation model (GCM), which incorporates a set of dubgrid-scale physics characterized by the Mellon-Yamada turbulence closure (hierarchy level 2.5), the Monin-Obukhov parameterization for the layer next to the ground surface, Manabe's cumulus parameterization, and the soil heat conduction. The sample cases adopted are for the month of January in the years from 1977 to 1983, which include the extraordinarily severe winter of 1977 and the most pronounced E1 Nino year of 1983. Each case is predicted by prescribing the climatologically normal sea surface temperature as the lower boundary conditions and by using an ensemble means of three individual integrations. These integrations start with three different initial conditions based on the Level data generated separately at the Geophysical Fluid Dynamics Laboratory, the National Meteorological Center, and the European Centre for Medium Range Weather Forecasts.

Miyakoda, K.↗
NASA NTRS2014

Application of Suomi-NPP Green Vegetation Fraction and NUCAPS for Improving Regional Numerical Weather Prediction

The NASA SPoRT Center is working to incorporate Suomi‐NPP products into its research and transition activities to improve regional numerical weather prediction (NWP). Specifically, SPoRT seeks to utilize two data products from NOAA/NESDIS: (1) daily global VIIRS green vegetation fraction (GVF), and (2) NOAA Unique CrIS and ATMS Processing System (NUCAPS) temperature and moisture retrieved profiles. The goal of (1) is to improve the representation of vegetation in the Noah land surface model (LSM) over existing climatological GVF datasets in order to improve the land‐atmosphere energy exchanges in NWP models and produce better temperature, moisture, and precipitation forecasts. The goal of (2) is to assimilate NUCAPS retrieved profiles into the Gridpoint Statistical Interpolation (GSI) data assimilation system to assess the impact on a summer pre‐frontal convection case. Most regional NWP applications make use of a monthly GVF climatology for use in the Noah LSM within the Weather Research and Forecasting (WRF) model. The GVF partitions incoming energy into direct surface heating/evaporation over bare soil versus evapotranspiration processes over vegetated surfaces. Misrepresentations of the fractional coverage of vegetation during anomalous weather/climate regimes (e.g., early/late bloom or freeze; drought) can lead to poor NWP model results when land‐atmosphere feedback is important. SPoRT has been producing a daily MODIS GVF product based on the University of Wisconsin Direct Broadcast swaths of Normalized Difference Vegetation Index (NDVI). While positive impacts have been demonstrated in the WRF model for some cases, the reflectances composing these NDVI do not correct for atmospheric aerosols nor satellite view angle, resulting in temporal noisiness at certain locations (especially heavy vegetation). The method behind the NESDIS VIIRS GVF is expected to alleviate the issues seen in the MODIS GVF real‐time product, thereby offering a higher‐quality dataset for modeling applications. SPoRT is evaluating the VIIRS GVF data against the MODIS real‐time and climatology GVF in both WRF and the NASA Land Information System. SPoRT has a history of assimilating hyperspectral infrared retrieved profiles

Numerical Weather Prediction↗
NASA NTRS2010

Using Remotely Sensed Data to Map Urban Vulnerability to Heat

This slide presentation defines remote sensing, and presents examples of remote sensing and astronaut photography, which has been a part of many space missions. The presentation then reviews the project aimed at analyzing urban vulnerability to climate change, which is to test the hypotheses that Exposure to excessively warm weather threatens human health in all types of climate regimes; Heat kills and sickens multitudes of people around the globe every year -- directly and indirectly, and Climate change, coupled with urban development, will impact human health. Using Multiple Endmember Spectral Mixing Analysis (MESMA), and the Phoenix urban area as the example, the Normalized Difference Vegetation Index (NDVI) is calculated, a change detection analysis is shown, and surface temperature is shown.

Stefanov, William L.↗
NASA NTRS2011

Preliminary Examination of Particles Recovered from the Surface of the Asteroid Itokawa by the Hayabusa Mission

The Hayabusa spacecraft arrived at S-type Asteroid 25143 Itokawa in November 2006, and reveal astounding features of the small asteroid (535 x 294 x 209 m). Near-infrared spectral shape indicates that the surface of this body has an olivinerich mineral assemblage potentially similar to that of LL5 or LL6 chondrites with different degrees of space weathering. Based on the surface morphological features observed in high-resolution images of Itokawa s surface, two major types of boulders were distinguished: rounded and angular boulders. Rounded boulders seem to be breccias, while angular boulders seem to have severe impact origin. Although the sample collection did not be made by normal operations, it was considered that some amount of samples, probably small particles of regolith, was collected from MUSES-C regio on the Itokawa s surface. The sample capsule was successfully recovered on the earth on June 13, 2010, and was opened at curation facility of JAXA (Japan Aerospace Exploration Agency), Sagamihara, Japan. A large number of small particles were found in the sample container. Preliminary analysis with SEM/EDX at the curation facility showed that at least more than 1500 grains were identified as rocky particles, and most of them were judged to be of extraterrestrial origin, and definitely from Asteroid Itokawa. Minerals (olivine, low-Ca pyroxene, high-Ca pyroxene, plagioclase, Fe sulfide, Fe-Ni metal, chromite, Ca phosphate), roughly estimated mode the minerals and rough measurement of the chemical compositions of the silicates show that these particles are roughly similar to LL chondrites. Although their size are mostly less than 10 m, some larger particles of about 100 m or larger were also identified. A part of the sample (probably several tens particles) will be selected by Hayabusa sample curation team and examined preliminary in Japan within one year after the sample recovery in prior to detailed analysis phase. Hayabusa Asteroidal Sample Preliminary Examination Team (HASPET) has been preparing for the preliminary examination with close cooperation with the curation team.

Tsuchiyama, A.↗
NASA NTRS1982

Investigation of advanced navigation and guidance system concepts for all-weather rotorcraft operations

Results are presented of a survey conducted of active helicopter operators to determine the extent to which they wish to operate in IMC conditions, the visibility limits under which they would operate, the revenue benefits to be gained, and the percent of aircraft cost they would pay for such increased capability. Candidate systems were examined for capability to meet the requirements of a mission model constructed to represent the modes of flight normally encountered in low visibility conditions. Recommendations are made for development of high resolution radar, simulation of the control display system for steep approaches, and for development of an obstacle sensing system for detecting wires. A cost feasibility analysis is included.

Upton, H. W.↗
DOE OSTI2023

The Impact of Circumsolar Diffuse Radiation on the Numerical Computation and Forecasting of DNI

Weather Research and Forecasting model with solar extensions (WRF-Solar) uses the Fast All-sky Radiation Model for Solar applications (FARMS) to predict solar radiation from the forecasted atmospheric gases, aerosols, and clouds. The Beer-Bouguer-Lambert law utilized by FARMS as well as other radiative transfer models assumes Direct Normal Irradiance (DNI) is a narrow beam only covering the sun disk. This assumption is interpreted differently in solar observations by pyrheliometers where the circumsolar diffuse radiation is accounted. This study precisely computes circumsolar diffuse radiation in all-sky conditions using a radiative transfer model based on a parameterization of precomputed cloud transmittance and reflectance. The model is implemented in WRF-Solar to provide day-ahead DNI forecast in the north America. The computation and forecasting of DNI is compared with the Beer-Bouguer-Lambert law to understand the impact of circumsolar diffuse radiation.

aerosols↗
DOE OSTI2022

Smoke from 2020 United States wildfires responsible for substantial solar energy forecast errors

Abstract The 2020 wildfire season (May through December) in the United States was exceptionally active, with the National Interagency Fire Center reporting over 10 million acres ( > 40 000 km 2 ) burned. During the September 2020 wildfire events, large concentrations of smoke particulates were emitted into the atmosphere. As a result, smoke was responsible for ∼10%–30% reduction in solar power production during peak hours as recorded by the California Independent System Operator (CAISO) sites. In this study, we focus on a 9 d period in September when wildfire smoke had a profound impact on solar energy production. During the smoke episodes, hour-ahead forecasts utilized by CAISO did not include the effects of smoke and therefore overestimated the expected power production by ∼10%–50%. Here we use multiple observational networks and a numerical weather prediction (NWP) model to show that the wildfire events of 2020 had a significantly detrimental influence on solar energy production due to high aerosol loading. We find that including the contribution of biomass burning particles greatly improves the day-ahead solar energy bias forecast of both global horizontal irradiance and direct normal irradiance by nearly ∼50%. Our results suggest that a more comprehensive treatment of aerosols, including biomass burning aerosols, in NWP models may be an important consideration for energy grid balancing, in addition to solar resource assessment, as solar power reliance increases.

14 SOLAR ENERGY↗